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BackgroundLittle data exists to guide the treatment of persistent COVID-19 in immunocompromised patients. We have employed a unique protocol combining tixegavimab/cilgavimab, and short-term combination antivirals including remdesivir.MethodsA retrospective single-center analysis of persistent COVID-19 in immunocompromised patients. Response was assessed by symptom resolution, declining C-reactive protein (CRP) levels and increasing SARS-CoV-2-PCR cycle-threshold (Ct) values.ResultsFourteen patients were included, including 2 kidney transplant recipients, 11 with B-cell lymphoproliferative disease, treated with anti-CD20 or ibrutinib, and 1 with rheumatoid arthritis, treated with anti-CD20. Median Ct-value was 27 (interquartile range (IQR):24-32). All patients received tixegavimab/cilgavimab and a 5-day course of remdesivir. Eleven also received nirmaltrevir/ritonavir and one received molnupiravir. Median follow-up was 45 days (IQR:12-89). Eleven patients had complete responses including symptom resolution, decrease in CRP, and increase in Ct values (all with either a negative PCR or Ct value>30 on day 4-16). Three patients had a partial response with relapses requiring re-admission. One had died, and two responded to prolonged antiviral treatments.ConclusionsA combination of monoclonal antibodies with antivirals has led to complete resolution of persistent COVID-19 in most severely-immunocompromised patients. Controlled studies will further direct the treatment of these patients, while more effective antivirals are urgently needed.Key pointsSome immunocompromised patients develop persistent symptomatic SARS-CoV-2 infection. Combination of monoclonal antibodies plus one or more antivirals cured 11/14 patients. Non-responders benefitted from prolonged combination antiviral treatment. Controlled trials are needed to find optimal treatment of persistent COVID-19.

Background Immunocompromised individuals (ICI) are at high risk for infections, some of which are preventable by vaccines. The Israeli MOH recommends PCV13 and PPSV23 vaccines for ICI, but vaccine coverage is suboptimal. The aim of this study was to assess the effectiveness of a project to improve pneumococcal vaccination (PV) rate among ICI in outpatient settings. Methods An automated validated, population-based registry of patients with ICI was developed in an Israeli health organization, Maccabi Healthcare Services, serving over 2.5 million members. Included in the registry were patients aged 18 and above, receiving immunosuppressive therapy (IT); patients living with HIV (PLWH); solid organ and bone marrow transplant recipients (TR); patients with advanced kidney disease (AKD); and patients with asplenia. Based on the registry and the Israeli MOH vaccination guidelines, a nationwide quality improvement project aimed at improving PV was implemented which began in October 2019. As part of the project, ICI were waived the need for preapproval for PCV13. During an eligible patient visit, physicians and nurses were prompted with an EHR alert reminding them to consider providing pneumococcal vaccine. In addition, eligible patients were invited via their patient health record (both desktop and mobile) to vaccinate. Vaccination rates during pre- and post-intervention periods were compared using the Chi square test. Results A total of 32,297 ICI were identified. Of them, 22,721 were on IT, 1651 PLWH, 1829 were TR ,5267 had AKD, and 1920 were asplenic. During the period October 2019 to October 2021, PCV13 vaccination rates went up from 12% to 54.1% (p< 0.0001), and PPSV23 vaccination rate improved from 44.7% to 62.6% (P < 0.0001). Conclusion Using one of the first real-world automated registries for ICI and implementation of targeted automated patient and provider alerts, markedly improved pneumococcal vaccine uptake was observed in this vulnerable population. Similar interventions may be used to increase the adherence for other vaccines, including COVID-19 vaccines. Disclosures Shirley Shapiro Ben David, MD, pfizer: Grant/Research Support Limor Adler, MD, pfizer: Grant/Research Support.

Facing the novel coronavirus disease (COVID-19) pandemic, evidence to inform decision-making at all care levels is essential. Based on the results of a study by Petrilli et al., we have developed a calculator using patient data at admission to predict critical illness (intensive care, mechanical ventilation, hospice care, or death). We report a retrospective validation of the calculator on 145 consecutive patients admitted with COVID-19 to a single hospital in Israel. Despite considerable differences between the original and validation study populations, of 18 patients with critical illness, 17 were correctly identified (sensitivity: 94.4%, 95% CI, 72.7%–99.9%; specificity: 81.9%, 95% CI, 74.1%–88.2%). Of 127 patients with non-critical illness, 104 were correctly identified. Our results indicate that published knowledge can be reliably applied to assess patient risk, potentially reducing the cognitive burden on physicians, and helping policymakers better prepare for future needs.

Facing the rapidly spreading novel coronavirus disease (COVID-19), evidence to inform decision-making at both the clinical and policy-making level is highly needed. Based on the results of a study by Petrilli et al, we have developed a calculator using patient data at admission to predict the risk of critical illness (intensive care unit admission, use of mechanical ventilation, discharge to hospice, or death).We report a retrospective validation of the risk calculator on 145 consecutive patients admitted with COVID-19 to a single hospital in Israel. Of the 18 patients with critical illness, 17 were correctly identified by the model(sensitivity: 94.4%, 95% CI, 72.7% to 99.9%; specificity: 81.9%, 95% CI, 74.1% to 88.2%). Of the 127 patients with non-critical illness, 104 were correctly identified. This, despite considerable differences between the original and validation study populations.Our results show that data from published knowledge can be used to provide reliable, patient level, automated risk assessment, potentially reducing the cognitive burden on physicians and helping policy makers better prepare for future needs.

Background The effects of an intervention on patients from populations other than that included in a trial may vary as a result of differences in population features, treatment administration, or general setting. Determining the generalizability of a trial to a target population is important in clinical decision making at both the individual practitioner and policy-making levels. However, awareness to the challenges associated with the assessment of generalizability of trials is low and tools to facilitate such assessment are lacking. Methods We review the main factors affecting the generalizability of a clinical trial results beyond the trial population. We then propose a framework for a standardized evaluation of parameters relevant to determining the external validity of clinical trials to produce a “generalizability score”. We then apply this framework to populations of patients with heart failure included in trials, cohorts and registries to demonstrate the use of the generalizability score and its graphic representation along three dimensions: participants’ demographics, their clinical profile and intervention setting. We use the generalizability score to compare a single trial to multiple “target” clinical scenarios. Additionally, we present the generalizability score of several studies with regard to a single “target” population. Results Similarity indices vary considerably between trials and target population, but inconsistent reporting of participant characteristics limit head-to-head comparisons. Conclusion We discuss the challenges involved in performing automatic assessment of trial generalizability at scale and propose the adoption of a standard format for reporting the characteristics of trial participants to enable better interpretation of their results.

Historically, guidelines for blood pressure measurement recommended adjusting the cuff deflation rate to the patient's heart rate (2-3 mmHg per heartbeat).Current guidelines recommend a fixed cuff deflation rate of 2 mmHg/sec.. In this study, we assess the association between pulse rate (PR) and BP variability. All BP measurements in adult patients with corresponding PR documentation were reviewed in a large outpatient database. In each category (6 categories between 40 and 99 bpm), patients with at least 3 BP readings within that category were included. In each category, systolic and diastolic BP coefficient of variance (corrected for sample size) was plotted against the PR category. There were 551,595 unique patients with a total of 4,760,000 measurements, and 860,522 groups of 3 measurements or more per patient within a PR category. BP normalized coefficient of variance was inversely related to PR (Figure), ranging 0.0043 to 0.0003 (Systolic), and 0.0024 to 0.0002 (Diastolic), for the lowest to highest heart rate category, respectively. BP variability is inversely associated with PR, especially in lower PR, likely reflecting less precise BP measurements where the "sample size" of pulse is small. The observed effect compromising precision might be accompanied by a concomitant reduced accuracy of BP measurement which is another theoretical implication of a smaller "sample size", leading to a systematic bias towards measuring lower and higher than real systolic and diastolic BP respectively.

Irreversible electroporation (IRE) damages cell membranes and is used in medicine for nonthermal ablation of malignant tumours. Our aim was to evaluate the antimicrobial effect of IRE. The pathogenic micro-organisms, Staphylococcus aureus, Streptococcus pyogenes, Escherichia coli, Pseudomonas aeruginosa and Candida albicans were subjected to IRE. Survival was measured as a function of voltage and the number of pulses applied. Combined use of IRE and oxacillin for eradication of Staph. aureus was also tested. Log10 reduction in micro-organisms positively correlated with the number of applied pulses. The colony count of Strep. pyogenes and E. coli declined by 3·38 and 3·05 orders of magnitude, respectively, using an electric field of 2000 V and 100 pulses. Killing of Staph. aureus and P. aeruginosa was achieved with a double cycle of IRE (2000, 1500 V and repeated 1250 V respectively) of 50-100 IRE pulses. The addition of subclinical inhibitory concentrations of oxacillin to the Staph. aureus suspension prior to IRE led to total bacterial death, demonstrating synergism between oxacillin and IRE. Our results demonstrate that using IRE with clinically established parameters has a marked in vitro effect on pathogenic micro-organisms and highlights the potential of IRE as a treatment modality for deep-seated infections, particularly when combined with low doses of antibiotics. Significance and impact of the study Irreversible electroporation (IRE) is utilized in interventional radiology to treat cancer patients. In this study we evaluated in vitro the antimicrobial effect of IRE. We demonstrated that using IRE with clinically established parameters has a marked effect on pathogenic micro-organisms and is synergistic to antimicrobials when both are combined. Our results point to the potential of IRE as a treatment modality for deep-seated infections.

ObjectiveMetformin is the recommended initial drug treatment in type 2 Diabetes Mellitus, but there is no clearly preferred choice for an additional drug when indicated. We use electronic health records to infer the counterfactual drug effectiveness in reducing HbA1c levels and effect on body-mass index (BMI) of four second line diabetes drug classes.Study design and settingRetrospective analysis of the electronic health records of US-based patients in the Explorys database using causal inference methodology to adjust for censored patients and confounders.Participants and ExposuresOur cohort consisted of roughly 25,000 patients with type 2 diabetes, prescribed metformin along with a drug out of four second line drug classes – sulfonylureas, thiazolidinediones, DPP-4 inhibitors and GLP-1 agonists, during the years 2000-2013.Main outcome measuresGlycated hemoglobin (HbA1c) and BMI of these patients after six and twelve months of treatment.ResultsWe show that all four drug classes reduce glycated hemoglobin levels, but the effect of sulfonylureas after 12 months of treatment is less pronounced compared to other classes. We also predict that thiazolidinediones increase body weight while DPP-4 inhibitors decrease it.ConclusionOur results are in line with current knowledge on second line drug effectiveness and effect on BMI. They demonstrate that causal inference from Electronic health records is an effective way for conducting multi-treatment causal inference studies.

Our first commitment as clinicians is to our patients as individuals. This understanding lies at the heart of the precision medicine initiative, which aims to customize treatments based not only on a patient’s clinical picture but also on their genetic, demographic and environmental profile.[1][1

Background There are several empiric antibiotic treatment options for febrile neutropenia, yet there is no universally-accepted initial protocol. We aimed to assess the performance of a protocol (piperacillin, gentamicin and cefazolin) introduced over 40 years ago and compare its coverage against bacteria isolated from blood of neutropenic patients with that of various commonly used antibiotic treatment protocols. Methods Adults with neutropenia admitted between 2003 and 2012 to the hemato-oncologic departments and in whom blood cultures were taken on admission were included. Appropriateness of several common antibiotic protocols was assessed based on the susceptibility of the blood isolates. Crude mortality rates were computed by the susceptibility of bacteria isolated from patients' blood to the actual treatment given. Results In total, 180 admissions of neutropenic patients (95 in patients who had fever above 38 °C) with positive blood cultures were analyzed. The actual antibiotic regimen prescribed was deemed appropriate in 82% of bacteremia episodes. The recommended institutional protocol was used in 62% of bacteremia episodes in neutropenic patients. This protocol would have been appropriate in 85% of all neutropenic bacteremia episodes and 89% of episodes in febrile neutropenia patients compared with piperacillin/tazobactam (79%, P = 0.13 and 76%, P = 0.002, respectively) and imipenem (93%, P = 0.004 and 92%, P = 0.74, respectively). Isolation of bacteria resistant to the actual antibiotic treatment given was associated with higher mortality at one week and at 30 days. Conclusion Common current antibiotic regimens provide similar coverage among febrile neutropenic patients, whereas broad spectrum antibiotic combinations maximize coverage among neutropenic patients.

Background Epidemiological features of infective endocarditis have changed during the last decades because of increases in the prevalence of health care exposure and of Staphylococcus aureus bloodstream infection. Consequently, the role of surgery is evolving. We aim to provide a contemporary profile of epidemiological, microbiological, and clinical features of infective endocarditis in a tertiary medical center, and identify predictors of mortality. Methods A prospective observational cohort study of consecutive adult patients with definite endocarditis according to the modified Duke criteria. Data were collected from January 1, 2009 through October 31, 2011 following a predefined case report form designed by the ICE-PCS. Results Among 70 endocarditis episodes, 25.7% involved prosthetic valves and 11.5% were device related. Forty-four percent of episodes were health-care associated. The predominant causative microorganism on native valve, prosthetic valve and device related endocarditis was Staphylococcus aureus (33.3%). Viridans group streptococci accounted for the majority of community-acquired endocarditis (36.1%). At least one complication occurred in 50% of the episodes. One third of the patients who had an indication for surgery were operated upon. Six month case fatality ratio was 40%. Sixty-five percent of patients with a contraindication to surgery died, compared with 9% and 28.5% who were treated surgically and medically, respectively. In multivariable analysis, age was a predictor of mortality. Conclusion Compared with other series, we observed more health-care associated endocarditis, and a higher mortality. Nearly half of all deaths were in patients who had a contraindication to surgery. Careful evaluation of contraindications to surgery is warranted.

Background ClinicalTrials.gov is valuable for aggregate-level analysis of trials. The recently published final rule aims to improve reporting of trial results. We aimed to assess variability in ClinicalTirals.gov records reporting participants’ baseline measures. Methods and findings The September 2015 edition of the database for Aggregate Analysis of ClinicalTrials.gov (AACT), was used in this study. To date, AACT contains 186,941 trials of which 16,660 trials reporting baseline (participant) measures were analyzed. We also analyzed a subset of 13,818 Highly Likely Applicable Clinical Trials (HLACT), for which reporting of results is likely mandatory and compared a random sample of 30 trial records to their journal articles. We report counts for each mandatory baseline measure and variability reporting in their formats. The AACT dataset contains 8,161 baseline measures with 1206 unique measurement units. However, of these 6,940 (85%) variables appear only once in the dataset. Age and Gender are reported using many different formats (178 and 49 respectively). “Age” as the variable name is reported in 60 different formats. HLACT subset reports measures using 3,931 variables. The most frequent Age format (i.e. mean (years) ± sd) is found in only 45% of trials. Overall only 4 baseline measures (Region of Enrollment, Age, Number of Participants, and Gender) are reported by > 10% of trials. Discrepancies are found in both the types and formats of ClinicalTrials.gov records and their corresponding journal articles. On average, journal articles include twice the number of baseline measures (13.6±7.1 (sd) vs. 6.6±7.6) when compared to the ClinicalTrials.gov records that report any results. Conclusions We found marked variability in baseline measures reporting. This is not addressed by the final rule. To support secondary use of ClinicalTrials.gov, a uniform format for baseline measures reporting is warranted.

Uncertainty is involved in each and every step of the diagnostic process. Trying to eliminate doubt altogether is too costly, is likely to fail, and may lead to patient harm. Acknowledging this, the threshold approach aims to optimize diagnosis-making by adopting the explicit use of probability estimates and by discouraging the pursuit of 100% certainty. Yet physicians are affected by cognitive biases which compromise their probabilistic reasoning and may lead to unreliable estimates. Health informatics tools helping to overcome human limitations by empowering physicians to handle probabilities are needed to increase the efficiency of diagnostic process.

Background Host factors and complications have been associated with higher mortality in infective endocarditis ( IE ). We sought to develop and validate a model of clinical characteristics to predict 6‐month mortality in IE . Methods and Results Using a large multinational prospective registry of definite IE (International Collaboration on Endocarditis [ ICE ]–Prospective Cohort Study [ PCS ], 2000–2006, n=4049), a model to predict 6‐month survival was developed by Cox proportional hazards modeling with inverse probability weighting for surgery treatment and was internally validated by the bootstrapping method. This model was externally validated in an independent prospective registry ( ICE ‐ PLUS , 2008–2012, n=1197). The 6‐month mortality was 971 of 4049 (24.0%) in the ICE ‐ PCS cohort and 342 of 1197 (28.6%) in the ICE ‐ PLUS cohort. Surgery during the index hospitalization was performed in 48.1% and 54.0% of the cohorts, respectively. In the derivation model, variables related to host factors (age, dialysis), IE characteristics (prosthetic or nosocomial IE , causative organism, left‐sided valve vegetation), and IE complications (severe heart failure, stroke, paravalvular complication, and persistent bacteremia) were independently associated with 6‐month mortality, and surgery was associated with a lower risk of mortality (Harrell's C statistic 0.715). In the validation model, these variables had similar hazard ratios (Harrell's C statistic 0.682), with a similar, independent benefit of surgery (hazard ratio 0.74, 95% CI 0.62–0.89). A simplified risk model was developed by weight adjustment of these variables. Conclusions Six‐month mortality after IE is ≈25% and is predicted by host factors, IE characteristics, and IE complications. Surgery during the index hospitalization is associated with lower mortality but is performed less frequently in the highest risk patients. A simplified risk model may be used to identify specific risk subgroups in IE .

Telehealth is the use of technology for remote patient monitoring and care. Wearables are small electronic devices that can seamlessly collect data about a patient for prolonged periods of time and support the implementation of telemedicine in the patient’s natural environment. In a reality where patients are becoming older and sicker, medicine is becoming more and more a multidisciplinary team work and healthcare resources are limited, telehealth holds promise as a way to improve patient care while cutting on costs. It may improve coordination between care providers, allow for bringing top notch expertise to remote, rural settings, provide a more complete picture of the patient’s condition and support independent living of the elderly and patients with chronic diseases. In this chapter, we review some of the related technology and application and portrait how they may be integrated in the near future in the healthcare delivery system.

BACKGROUND Antihypertensive β-blocker use is associated with greater intervisit blood pressure variability (BPV) and with less favorable outcomes compared to other antihypertensive agents. A theoretical model demonstrated that accuracy and precision of BP measurement are affected by heart rate (HR) at a constant cuff deflation rate. We aimed to examine the empirical relationship between HR and BPV in a clinical setting. METHODS Intratracing variability in ambulatory BP monitoring (ABPM) were analyzed in search of a link between BPV and HR. BPV was expressed as standard deviation (s.d.), coefficient of variation (CV), and variability independent of the mean (VIM). RESULTS In a dataset of 4,693 subjects, HR was inversely associated with BPV and independently explained 1.3% of between-subject variation in s.d. of awake systolic BP (1.5% of CV and VIM). Linear regression suggested 0.5 mm Hg increase in s.d. of systolic BP per 10 beats per minute (bpm) decrease in HR. In a subset of 1,019 patients with available data on medications, HR was independently and inversely related with awake systolic BPV (P < 0.0001), more so in diuretic (P < 0.050) and renin-angiotensin system antagonists-treated (P < 0.050) patients. Associations of β-blockade with increased BPV were abolished by model-adjustment for HR. In another subset of patients who were monitored twice (n = 635), HR had a mild (0.6%) but significant (P < 0.05) inverse contribution to the change in awake systolic BPV between repeated monitoring. CONCLUSIONS Ambulatory BPV is inversely related to HR and is not increased in referred patients treated with β-blockers after correction for HR.

As the volume and variety of healthcare related data continues to grow, the analysis and use of this data will increasingly depend on the ability to appropriately collect, curate and integrate disparate data from many different sources. We describe our approach to and highlight our experiences with the development of a robust data collection, curation and integration infrastructure that supports healthcare analytics. This system has been successfully applied to the processing of a variety of data types including clinical data from electronic health records and observational studies, genomic data, microbiomic data, self-reported data from surveys and self-tracked data from wearable devices from over 600 subjects. The curated data is currently being used to support healthcare analytic applications such as data visualization, patient stratification and predictive modeling.

Objective Metformin is the recommended initial drug treatment in type 2 diabetes mellitus, but there is no clearly preferred choice for an additional drug when indicated. We compare the counterfactual drug effectiveness in lowering glycated hemoglobin (HbA1c) levels and effect on body mass index (BMI) of four diabetes second-line drug classes using electronic health records. Study design and setting Retrospective analysis of electronic health records of US-based patients in the Explorys database using causal inference methodology to adjust for patient censoring and confounders. Participants and exposures Our cohort consisted of more than 40 000 patients with type 2 diabetes, prescribed metformin along with a drug out of four second-line drug classes—sulfonylureas, thiazolidinediones, dipeptidyl peptidase 4 (DPP-4) inhibitors and glucagon-like peptide-1 agonists—during the years 2000–2015. Roughly, 17 000 of these patients were followed for 12 months after being prescribed a second-line drug. Main outcome measures HbA1c and BMI of these patients after 6 and 12 months following treatment. Results We demonstrate that all four drug classes reduce HbA1c levels, but the effect of sulfonylureas after 6 and 12 months of treatment is less pronounced compared with other classes. We also estimate that DPP-4 inhibitors decrease body weight significantly more than sulfonylureas and thiazolidinediones. Conclusion Our results are in line with current knowledge on second-line drug effectiveness and effect on BMI. They demonstrate that causal inference from electronic health records is an effective way for conducting multitreatment causal inference studies.

To the Editor: In their recent article in Hypertension , Muntner et al1 examined the correlates and prognostic significance of intervisit blood pressure (BP) variability in Third National Health and Nutrition Examination Survey participants. They report that increased intervisit variability was related to age, physical inactivity, BP, laboratory abnormalities, comorbid conditions, and prescribed medications. Independent of these associations, systolic intervisit variability was found to …

OBJECTIVE Overactivity of the Forkhead transcription factor FoxO1 promotes diabetic hyperglycemia, dyslipidemia, and acute-phase response, whereas suppression of FoxO1 activity by insulin may alleviate diabetes. The reported efficacy of long-chain fatty acyl (LCFA) analogs of the MEDICA series in activating AMP-activated protein kinase (AMPK) and in treating animal models of diabesity may indicate suppression of FoxO1 activity. RESEARCH DESIGN AND METHODS The insulin-sensitizing and anti-inflammatory efficacy of a MEDICA analog has been verified in guinea pig and in human C-reactive protein (hCRP) transgenic mice, respectively. Suppression of FoxO1 transcriptional activity has been verified in the context of FoxO1- and STAT3-responsive genes and compared with suppression of FoxO1 activity by insulin and metformin. RESULTS Treatment with MEDICA analog resulted in total body sensitization to insulin, suppression of lipopolysaccharide-induced hCRP and interleukin-6–induced acute phase reactants and robust decrease in FoxO1 transcriptional activity and in coactivation of STAT3. Suppression of FoxO1 activity was accounted for by its nuclear export by MEDICA-activated AMPK, complemented by inhibition of nuclear FoxO1 transcriptional activity by MEDICA-induced C/EBPβ isoforms. Similarly, insulin treatment resulted in nuclear exclusion of FoxO1 and further suppression of its nuclear activity by insulin-induced C/EBPβ isoforms. In contrast, FoxO1 suppression by metformin was essentially accounted for by its nuclear export by metformin-activated AMPK. CONCLUSIONS Suppression of FoxO1 activity by MEDICA analogs may partly account for their antidiabetic anti-inflammatory efficacy. FoxO1 suppression by LCFA analogs may provide a molecular rational for the beneficial efficacy of carbohydrate-restricted ketogenic diets in treating diabetes.

Blood pressure (BP) assessment may be vulnerable to bias by increased BP variability. Uncertainty in determining BP control is inherent to the clinic setting. We analyzed a registry of 3949 patients referred for ambulatory BP monitoring. The difference between clinic and ambulatory readings was plotted against ambulatory BP variability, assessed by standard deviation. In addition, BP variability of patients with clinic and awake ambulatory hypertension was compared with that of patients with controlled BP and sustained hypertension, respectively. The average clinic-ambulatory systolic BP difference was 5 ± 17/3 ± 9 mm Hg. Patients with10-mm Hg systolic difference had higher systolic ambulatory BP standard deviation (14.9 ± 4.2 mm Hg) compared to patients with a difference of 0 to 10-mm Hg (standard deviation 12.5 ± 3.7 mm Hg). Patients with masking (negative clinic-ambulatory BP difference) also had comparatively higher standard deviation (14.4 ± 4.9 mm Hg P0.0001). Greater ambulatory BP variability carried increased risk for both false diagnosis of hypertension (odds ratio (OR): 2.09, 95% confidence interval (CI): 1.58-2.76), and missed clinic diagnosis of hypertension (OR: 1.86, 95% confidence interval: 1.48-2.33). The former was more striking in women, in whom high variability carried greater odds for false diagnosis of hypertension (OR: 2.76, 95% confidence interval: 1.96-3.89). Thus, clinic misjudgment of BP control may stem in part from high BP variability. Women with high BP variability are more susceptible to hypertension misdiagnosis. It is possible that high BP variability contributes to the increased cardiovascular risk related to both masked hypertension and white coat hypertension.

Background and Objectives: In light of the increasing popularity of the threshold approach in clinical decision-making, this study assesses the role of expertise in physicians’ agreement in estimating the probability of disease in patients. Methods: A cross-sectional survey of physicians of different specialties, attending weekly staff meetings in four teaching hospitals in Jerusalem, Israel. An anonymous questionnaire describing three case scenarios of patients with chest pain was administered and participants were asked to estimate pretest probabilities of disease. Results: Eighty-six physicians (practicing cardiology, internal medicine, and family medicine, as well as general practitioners and internists) out of 125 approached (response rate 69%). The mean estimated probabilities were very similar for residents and specialists; however, the standard deviation was higher for specialists in all three cases: 20.7, 21.0, and 19.1 among specialists and 16.4, 20.5, and 14.9 among residents, respectively. Conclusion: This study, based on case scenarios, did not find that medical expertise improved agreement among doctors when estimating the probability of disease in patientsddespite the common belief that senior physicians should have smaller interobserver differences in probability estimates. The wide variation observed calls into question the applicability of the threshold approach. 2005

Background: The ‘threshold approach’ is based on a physician’s assessment of the likelihood of a disease expressed as a probability. The use of Bayes’ theorem to calculate disease probability in patients with and without a particular characteristic, may be hampered by the presence of subadditivity (i.e. the sum of probabilities concerning a single case scenario exceeding 100%). Aim: To assess the presence of subadditivity in physicians’ estimations of probabilities and the degree of concordance among doctors in their probability assessments. Design: Prospective questionnaire. Methods: Residents and trained physicians in Family Medicine, Internal Medicine and Cardiology ( n = 84) were asked to estimate the probability of each component of the differential diagnosis in a case scenario describing a patient with chest pain . Results: Subadditivity was exhibited in 65% of the participants. The total sum of probabilities given by each participant ranged from 44% to 290% (mean 137%). There was wide variability in the assignment of probabilities for each diagnostic possibility (SD 16–21%). Discussion: The finding of substantial subadditivity, coupled with the marked discordance in probability estimates, questions the applicability of the threshold approach. Physicians need guidance, explicit tools and formal training in probability estimation to optimize the use of this approach in clinical practice.

To the Editor:— Readers ofThe Journalwho wish to send blood specimens through the mail for blood group antigen and antibodies studies may find some use for the fluid here described. It consists of equal parts of whole blood and Alsever's solution, with a drop of penicillin and streptomycin to give a final concentration of about 30 units and 0.005 mg. per milliliter respectively. With the use of sterile technique the blood is drawn directly into the Alsever's solution, the antibiotic is added promptly, and the container is sealed with a rubber bung for best results. Since November, 1952, I have used this fluid to prepare a diagnostic panel of red cells (PANOCELL), which is shipped unrefrigerated throughout the United States every two weeks via air mail. Recently about 450 different blood specimens were sent in this way from New York to London for blood group studies. All of